Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis.

Journal: Epilepsy & behavior : E&B
PMID:

Abstract

BACKGROUND AND OBJECTIVES: to identify predictors of progression to refractory status epilepticus (RSE) using a machine learning technique.

Authors

  • Stefano Meletti
    Neurophysiology Unit and Epilepsy Centre, Azienda Ospedaliera-Universitaria di Modena, Italy; Dept of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio-Emilia, Italy. Electronic address: stefano.meletti@unimore.it.
  • Giada Giovannini
    Neurophysiology Unit and Epilepsy Centre, Azienda Ospedaliera-Universitaria di Modena, Italy; University of Modena and Reggio-Emilia, PhD Programm in Clinical and Experimental Medicine, Modena, Italy.
  • Simona Lattanzi
    Marche Polytechnic University, Neurological Clinic, Department of Experimental and Clinical Medicine, Ancona, Italy.
  • Arian Zaboli
    Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), Bolzano, Italy. Electronic address: zaboliarian@gmail.com.
  • Niccolò Orlandi
    Neurophysiology Unit and Epilepsy Centre, Azienda Ospedaliera-Universitaria di Modena, Italy; Dept of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio-Emilia, Italy.
  • Gianni Turcato
    Department of Emergency Medicine, Franz Tappeiner Hospital, Merano, Italy.
  • Francesco Brigo
    Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), Bolzano, Italy.